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Keyframer

Get a recipe (scene + code)

get_recipe
Read-only

Fetch one recipe by slug: metadata, the scene JSON (usable as a starting point for create_scene), and the generated React Native Reanimated component code. Recipe code is free to use.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoAlias for slug — a scene id from a recipe works too
slugNoRecipe slug from search_recipes
scene_idNoWhen a recipe has several scenes, pick one (defaults to the first)
include_codeNoInclude generated code (default true)

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond that: it specifies the return payload (metadata, scene JSON, generated React Native Reanimated code), says the scene JSON can seed create_scene, and clarifies licensing with 'Recipe code is free to use.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences front-load the action and resource, then pack the payload and licensing into the second sentence. There is no filler or redundant restating of the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only single-resource fetch with a fully documented schema, the description states the return payload, the integration point with create_scene, and usage rights. With readOnlyHint and 100% schema coverage, nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers all four parameters with descriptions, so the baseline 3 applies. The description confirms slug as the lookup key and only implicitly reflects include_code's effect; it adds no syntax or format detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Begins with 'Fetch one recipe by slug', naming a specific verb, resource, and key identifier. It enumerates the payload (metadata, scene JSON, React Native Reanimated code), and the mention of create_scene separates recipes from plain scenes. This distinguishes it well from get_scene and search_recipes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'one recipe by slug' plus the parameter note that slug comes from search_recipes gives a clear retrieval context. Though the description does not explicitly name alternatives or when-not conditions, no exclusions are needed for such a straightforward fetch.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct resource or action: scene CRUD, validation, motion sampling, recipe lookup, code generation, and QR preview. Potential pairs like validate_scene vs sample_scene are clearly separated as structural validation vs motion evaluation, and get_scene vs get_recipe differ by source and purpose.

Naming Consistency5/5

Tool names consistently follow a verb_noun snake_case pattern: create_scene, get_scene, list_scenes, update_scene, validate_scene, search_recipes. The few compound nouns like get_preview_qr and get_scene_format still fit the same predictable convention.

Tool Count5/5

11 tools is well within the ideal range and each tool serves a clear part of the scene authoring workflow: discovery, validation, sampling, editing, compiling, and previewing. None feel redundant or extraneous for the stated purpose.

Completeness4/5

The toolset covers the core scene lifecycle well: create, read, list, update, validate, sample, generate code, and preview. The main gap is the absence of a delete_scene tool, which is a minor omission since the authoring and iteration workflow is otherwise fully supported.

Resources